Comprehensive Analysis of the Mitochondrial Genome of Grimmia tergestina: Codon Usage Bias, RNA Editing, and Organelle DNA Transfer

Comprehensive Analysis of the Mitochondrial Genome of Grimmia tergestina: Codon Usage Bias, RNA Editing, and Organelle DNA Transfer | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comprehensive Analysis of the Mitochondrial Genome of Grimmia tergestina: Codon Usage Bias, RNA Editing, and Organelle DNA Transfer Xiaojuan Li, Hengyu Dai, Shouqiang Li, Huakun Zhou, Jiuli Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9311791/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background Grimmia tergestina Tomm. ex Bruch & Schimp. is a perennial xerophytic moss adapted to exposed rocky habitats, yet its mitochondrial genome architecture and associated post-transcriptional and inter-organellar evolutionary features remain poorly characterized. This study aimed to assemble and characterize the complete mitochondrial genome of Grimmia tergestina and to examine its codon usage bias, RNA editing, repetitive sequences, phylogenetic position, and homologous sequence transfer between mitochondrial and chloroplast genomes. Results The complete mitochondrial genome of Grimmia tergestina is a circular molecule of 106,891 bp with a GC content of 39.77%. A total of 66 genes were annotated, including 39 protein-coding genes, 24 transfer RNA genes, and 3 ribosomal RNA genes; 15 genes contained 27 introns, and three copies of trnM-CAT were identified. Codon usage analysis showed a strong preference for A/U-ending codons, with UUA as the most frequently used optimal codon. A total of 133 predicted C-to-T RNA editing sites were detected in 34 of the 39 protein-coding genes, predominantly at the first and second codon positions, and many editing events altered amino-acid hydrophobicity. Repeat analysis identified 51 dispersed repeats, five tandem repeats, and 110 simple sequence repeats. Comparative analyses revealed several highly variable regions, including ccmFC–rps4 and nad6–cox2, and five loci with relatively high nucleotide diversity. Phylogenetic analysis recovered Grimmia tergestina as the basal lineage of the sampled Grimmiaceae, whereas Funaria hygrometrica and Physcomitrium patens formed a basal outgroup clade. In addition, 38 high-confidence homologous fragments were detected between mitochondrial and chloroplast genomes, most of which were rRNA-derived. Conclusions These results provide the first comprehensive mitochondrial genome resource for Grimmia tergestina and show that its organellar genome evolution is characterized by A/U-biased codon usage, abundant RNA editing, repeat-rich intergenic regions, and detectable chloroplast-to-mitochondrion sequence transfer. The study provides useful genomic evidence for future investigations of bryophyte molecular evolution, phylogeny, and organelle genome coordination. Grimmia tergestina mitochondrial genome codon usage bias RNA editing repetitive sequences organelle genome evolution bryophytes Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Background Bryophytes represent the second most species-rich group of land plants after angiosperms and are widely distributed in diverse habitats, including deserts, alpine ecosystems, and high-elevation regions. Their unique structural and physiological characteristics, such as tolerance to drought, cold, and nutrient-poor conditions, enable them to play crucial ecological roles in global ecosystems [ 1 ]. Species within the family Grimmiaceae are particularly adapted to semi-arid environments and are commonly found on exposed rocks or cliff surfaces in mountainous regions. Due to their distinctive morphological features and ecological specialization, these plants can provide important insights into plant floristic evolution and species diversification [ 2 ]. Grimmia tergestina Tomm. ex Bruch & Schimp., a perennial xerophytic moss species belonging to the genus Grimmia Hedw. within the family Grimmiaceae, commonly inhabits exposed rocky substrates in arid and semiarid environments, particularly in alpine or high-altitude regions [ 3 ]. Mitochondria are essential cellular organelles responsible for respiration, energy production, and numerous metabolic processes. Similar to chloroplasts, plant mitochondria possess their own genomes, which are thought to originate from ancient endosymbiotic events [ 4 – 7 ]. Plant mitochondrial genomes exhibit several distinctive characteristics, including large genome sizes, complex structural organization, extensive recombination, and frequent intracellular gene transfer events [ 8 – 11 ]. These features make mitochondrial genomes important resources for studying genome evolution, organellar interactions, and phylogenetic relationships among plant lineages. Chloroplast and mitochondrial genomes within the same species exhibit significant differences in genomic organization, sequence length, gene composition, and expression patterns. These differences are largely influenced by gene transfer events and functional replacement by nuclear genes. Mutation rates and structural variation patterns also differ between these genomes. For instance, the evolutionary rate of chloroplast genomes is approximately half that of nuclear genomes, whereas plant mitochondrial genomes evolve even more slowly [ 12 , 13 ]. Such characteristics have important implications for understanding evolutionary processes and reconstructing phylogenetic relationships. These variations may influence phylogenetic inference based on organellar genome data [ 14 ]. In addition, plant mitochondrial genomes often contain repetitive sequences and exhibit extensive RNA editing, both of which contribute to post-transcriptional regulation and protein diversity [ 15 , 16 ]. Codon usage bias is the preferential or non-random use of synonymous codons, a ubiquitous phenomenon observed in bacteria, plants, and animals [ 17 ]. Analysis of codon usage bias provides valuable insights into gene expression regulation, gene function prediction, genetic variation among species, and the mechanisms underlying molecular evolution [ 18 – 20 ]. Previous studies have shown that plant organellar genomes generally exhibit a preference for codons ending in A or U, reflecting the nucleotide composition bias of these genomes [ 21 ]. However, comprehensive investigations of codon usage bias in bryophyte mitochondrial genomes remain scarce. Furthermore, extensive gene transfer occurs between chloroplasts and mitochondria. This process involves not only intragenomic recombination within organelles, but also inter-organellar DNA transfer and gene transfer from organelles to the nucleus, known as “nuclear-organellar gene flow”. This phenomenon reflects the dynamic and continuous nature of life evolution and provides insights into how organisms adapt to environmental changes and optimize their physiological functions [ 14 ]. Although chloroplast-to-mitochondrion DNA transfer has been reported in several plant species, the extent and functional implications of such transfers in bryophytes remain poorly understood. The genus Grimmia (Grimmiaceae) comprises numerous species adapted to extreme environmental conditions, particularly in alpine and arid habitats. Despite their ecological significance, genomic resources for many Grimmia species remain limited. In particular, mitochondrial genomic data for this genus are still lacking, which hinders our understanding of mitochondrial genome evolution and organellar interactions in bryophytes. In this study, we assembled and characterized the complete mitochondrial genome of G. tergestina. We conducted comprehensive analyses of genome structure, gene content, codon usage bias, RNA editing sites, repetitive sequences, and phylogenetic relationships. In addition, we investigated homologous fragments between mitochondrial and chloroplast genomes to explore potential intracellular DNA transfer events. The results provide new insights into mitochondrial genome evolution and organelle genome interactions in bryophytes and contribute to a deeper understanding of the evolutionary mechanisms underlying early land plant diversification. Methods Sample collection and sequencing Wild samples of G. tergestina were collected in October 2024 from exposed alpine rocks along the southern bank of the Yellow River in Huangheqing National Wetland Park, Guide County, Qinghai Province, China (36.051258°N, 101.301659°E). Field sampling was conducted in accordance with local legislation, and no specific permission was required for the collection of this bryophyte material from the sampling site. The collected samples were formally identified as G. tergestina by Prof. Xueliang Bai, Inner Mongolia Normal University, China. A voucher specimen was deposited in the Sample Room of the Qinghai Provincial Biotechnology and Analytical Test Key Laboratory, Qinghai Minzu University, Xining, China, under voucher number HHQ2024001. Immediately after collection, samples were rapidly frozen in liquid nitrogen and transported on dry ice to Nanjing Jisi Huiyuan Biotechnology Co., Ltd. for organelle genome sequencing. Mitochondrial genomes were sequenced using the Illumina NovaSeq 6000 platform with paired-end sequencing (PE150 mode). Raw sequencing reads were quality filtered using Trimmomatic v0.39 with a Phred score threshold ≥ 30. High-quality reads were subsequently assembled using SPAdes v3.15.3. The circularity of the assembled mitochondrial genome was verified using Bandage v0.8.1 to ensure sequence completeness [ 22 , 23 ]. Genome assembly, annotation and visualization The complete mitochondrial genome of G. tergestina is 106,891 bp in length and has been deposited in the CNSA database under accession number CNS1408476. The genome contains 39 coding DNA sequences (CDS). Initial genome annotation was performed using the DOGMA program, followed by manual correction of start and stop codons as well as intron boundaries using Geneious v9.0.2 [ 24 , 25 ]. For codon usage bias analysis, coding sequences (CDS) longer than 300 bp were selected according to the following criteria: an ATG start codon, a valid stop codon, absence of internal stop codons, and no interference from repetitive sequences. The circular mitochondrial genome map was generated using the online tool OGDRAW. Codon usage bias analysis Codon usage parameters were calculated using CodonW v1.4.2. The following indices were used: CAI (Codon Adaptation Index), which was used to evaluate gene expression level and ranges from 0 to 1, with higher values indicating greater expression potential; RSCU (Relative Synonymous Codon Usage), which indicates codon preference when the value is greater than 1; and ENC (Effective Number of Codons), which measures codon bias and ranges from 20 (strong bias) to 61 (no bias). Identification of optimal codons When the RSCU value equals 1, codon usage is considered unbiased. Codons with RSCU values greater than 1 are defined as high-frequency codons, whereas those with values less than 1 are considered low-frequency codons. Optimal codons were identified based on RSCU values combined with codon usage patterns [ 26 ]. Phylogenetic analysis Complete mitochondrial genome sequences of nine species from Grimmiaceae and two species from Funariaceae were downloaded from the NCBI database for phylogenetic analysis. Sequence alignment was performed using MAFFT version 7.0 ( https://mafft.cbrc.jp/alignment/server/ ) [ 27 ]. A phylogenetic tree was constructed using the Neighbor-Joining (NJ) method implemented in MEGA7.0 with 1000 bootstrap replicates [ 28 ]. The final phylogenetic tree was visualized using OGDRAW ( https://chlorobox.mpimp-golm.mpg.de/OGDraw.html ) [ 29 ]. Table 1 Taxa included in phylogenetic analysis Subclass Order Family Genus Species Accession No. Genome Size Dicranidae Grimmiales Grimmiaceae Racomitrium Racomitrium elongatum KP687246.1 106746 bp Dicranidae Grimmiales Grimmiaceae Racomitrium Racomitrium ericoides KP233863.1 106727 bp Dicranidae Grimmiales Grimmiaceae Codriophorus Codriophorus varius KP687247.1 106358 bp Dicranidae Grimmiales Grimmiaceae Codriophorus Codriophorus aciculare KP453983.1 106818 bp Dicranidae Grimmiales Grimmiaceae Codriophorus Codriophorus laevigatus KM506905.1 106809 bp Dicranidae Grimmiales Grimmiaceae Bucklandiella Bucklandiella orthotrichacea KP742835.1 107215 bp Dicranidae Grimmiales Grimmiaceae Racomitrium Racomitrium emersum KP742836.1 107186 bp Dicranidae Grimmiales Grimmiaceae Racomitrium Racomitrium lanuginosum KU050083.1 106795 bp Dicranidae Grimmiales Grimmiaceae Grimmia Grimmia tergestina CNS1408476 106,891 bp Bryidae Funariales Funariaceae Funaria Funaria hygrometrica KC784959.1 109586 bp Funariidae Funariales Funariaceae Physcomitrium Physcomitrium patens KY126309.1 105340 bp Repeat sequence analysis Dispersed repeats in the mitochondrial genome were identified using the online tool REPuter with the following parameters: Hamming distance = 3 and minimum repeat size of 20 bp [ 30 ]. Four types of repeats were considered: forward (F), reverse (R), complement (C), and palindromic (P) repeats. Simple sequence repeats (SSRs) were identified using MISA with the following minimum repeat thresholds [ 31 ]: mononucleotide repeats ≥ 10, dinucleotide repeats ≥ 5, trinucleotide repeats ≥ 4, and tetra-, penta-, and hexanucleotide repeats ≥ 3 Comparative Analysis of Mitochondrial Genome Sequences of Grimmia tergestina and Its Related Taxa Genome similarity among related species was analyzed using the LAGAN mode in mVISTA, with the mitochondrial genome of G. tergestina used as the reference [ 32 ]. Nucleotide diversity analysis Multiple sequence alignment of mitochondrial genome sequences was performed using MAFFT 7.409 in a Linux environment. The aligned sequences were imported into DnaSP v6.12.03 for nucleotide diversity (Pi) analysis and visualization. Analysis of homologous sequences between mitochondrial and chloroplast genomes Homologous fragments between mitochondrial and chloroplast genomes were identified using BLAST implemented in TBtools. The filtering criteria were as follows: sequence identity ≥ 70%, E-value ≤ 1e-4, and alignment length ≥ 30 bp. Identified homologous fragments were visualized using Circos (v0.69-5). Results Mitochondrial genome structure and gene composition The mitochondrial genome of G. tergestina forms a typical circular molecule with a total length of 106,891 bp (Fig. 1 ). The overall GC content of the genome is 39.77%. Among different gene categories, the GC content of protein-coding genes (PCGs) (35.26%) was lower than that of tRNA genes (46.36%) and rRNA genes (47.24%). A total of 66 genes were annotated in the mitochondrial genome, including 39 protein-coding genes (PCGs), 24 tRNA genes, and 3 rRNA genes (Table 2 ). Among these genes, 15 genes contained introns, including atp1, atp6, atp9, ccmFC, cob, cox1, cox2, cox3, nad1, nad2, nad4, nad5, nad7, nad9, and sdh3, comprising 27 introns in total. Genes encoding NADH dehydrogenase subunits contained the largest number of introns (11 introns). Notably, three copies of the trnM-CAT gene were identified in the mitochondrial genome of G. tergestina , indicating a unique gene copy structure.Among the protein-coding genes, the most common start codon was ATG, and the most frequently observed stop codon was TAA. The 24 tRNA genes encode 18 of the 20 standard amino acids, including alanine (Ala), cysteine (Cys), aspartic acid (Asp), glutamic acid (Glu), phenylalanine (Phe), histidine (His), lysine (Lys), leucine (Leu), methionine (Met), proline (Pro), glutamine (Gln), arginine (Arg), serine (Ser), threonine (Thr), valine (Val), tryptophan (Trp), tyrosine (Tyr), and glycine (Gly). Some amino acids were encoded by two tRNA genes with different anticodons, such as trnG-GCC / trnG-TCC and trnR-ACG / trnR-TCT. Additionally, certain tRNA genes showed gene duplication, such as trnF-GAA and trnG-GCC, while trnM-CAT occurred in three copies, which may reflect lineage-specific copy-number variation or genomic organization. Table 2 Classification of the Mitochondrial Genome of Grimmia tergestina Group of genes Gene name Length Start codon Stop codon Amino acid ATP synthase atp 1* 1557 ATG TAA 519 atp 4* 552 ATG TGA 184 atp 6 759 ATG TAA 253 atp 8 525 ATG TGA 175 atp 9*** 225 ATG TAA 75 Cytochrome c biogenesis ccm B 528 ATG TAG 176 ccm C 759 ATG TAA 253 ccm FC* 1389 ATG TGA 463 ccm Fn 1830 ATG TAA 610 Ubichinol cytochrome c reductase cob * 1221 ATG TGA 407 Cytochrome c oxidase cox 1**** 1569 ATG TAG 523 cox 2*** 762 ATG TAA 254 cox 3* 798 ATG TAA 266 Transport membrane protein mtt B 735 ACG (ATG) TAA 245 NADH dehydrogenase nad 1** 987 ATG TAA 329 nad 2* 1470 ATG TAA 490 nad 3 357 ATG TAA 119 nad 4 1488 ATG TAA 496 nad 4L* 303 ATG TAA 101 nad 5*** 2031 ATG TAA 677 nad 6 606 ATG TGA 202 nad 7** 1182 ATG TAG 394 nad 9* 588 GTG (not determined/transl_except) TAA 196 Ribosomal proteins (LSU) rpl 10 540 ATG TAG 180 rpl 2 1395 ATG TAG 465 rpl 5 561 ATG TAG 187 rpl 6 306 ATG TAA 102 Ribosomal proteins (SSU) rps 1 810 ATG TAA 270 rps 11 357 ATG TAA 119 rps 12 381 ATG TGA 127 rps 13 369 ATG TGA 123 rps 14 300 ATG TAG 100 rps 19 282 ATG TAG 94 rps 2 726 ATG TAG 242 rps 3 1617 ATG TAA 539 rps 4 588 ATG TAA 196 rps 7 720 ATG TAA 240 Succinate dehydrogenase sdh 3* 396 ATG TAA 132 sdh 4 261 ATG TAA 87 Ribosomal RNAs rrn 18 1727 rrn 26 3356 rrn 5 122 Transfer RNAs trn A-TGC 73 trn C-GCA 71 trn D-GTC 74 trn E-TTC 73 trn F-GAA 74 trn G-GCC 72 trn G-TCC 71 trn H-GTG 73 trn K-TTT 73 trn L-CAA 80 trn L-TAA 80 trn L-TAG 85 trn M-CAT (3) (74, 73, 73) trn P-TGG 74 trn Q-TTG 72 trn R-ACG 74 trn R-TCT 74 trn S-TGA 84 trn T-GGT 73 trn V-TAC 73 trn W-CCA 73 trn Y-GTA 83 Codon usage bias A total of 30 codons exhibited RSCU values greater than 1, indicating preferential usage. Among these, 29 high-frequency codons ended with A or U, accounting for 96.7% (13 codons ended with A, accounting for 43.3%, and 16 codons ended with U, accounting for 53.3%), suggesting a strong A/U preference in synonymous codon selection. The most frequently used optimal codon was UUA, which encodes leucine (Leu). These results indicate that the mitochondrial genome of G. tergestina exhibits a pronounced A/U-ending codon preference, a pattern commonly observed in plant mitochondrial genomes and likely influenced by mutational pressure and translational selection. The schematic diagram of codon usage bias is shown in Fig. 2 . The boxes below represent all codons encoding each amino acid, and the height of the bars above indicates the sum of RSCU values for all codons. RNA editing site prediction A total of 133 RNA editing sites were predicted in 34 of the 39 protein-coding genes, and all of them were C-to-T editing events (Fig. 3 ). The number of predicted editing sites per gene ranged from 1 to 13. Among all genes, rps3 contained the highest number of predicted editing sites (13), followed by ccmFC and rpl2 (10 each), ccmFn (9), atp8 (8), mttB (7), and sdh3 (6). Most of the remaining genes contained only 1–5 editing sites, whereas no predicted editing sites were detected in five protein-coding genes. The RNA editing events were classified into five categories according to the hydrophilicity of the amino acid changes (Table 3 ). Among them, hydrophilic-to-hydrophobic conversions were the most frequent (42.11%), followed by hydrophobic-to-hydrophobic conversions (39.10%), hydrophobic-to-hydrophilic conversions (12.78%), and hydrophilic-to-hydrophilic conversions (5.26%). Only one predicted editing event (0.75%) generated a premature termination codon. A total of 29 codon transition types were identified, among which CTT (L)→TTT (F) was the most frequent, occurring 15 times. RNA editing mainly affected the first and second codon positions, and a small number of codon transitions involved simultaneous changes at both positions. Overall, RNA editing resulted in the greatest increase in phenylalanine, including 20 conversions from leucine, 15 from serine, and 4 from proline. Table 3 Classification of RNA Editing Sites Type RNA-editing Count Percentage Hydrophilicity → Hydrophilicity CAC (H) → TAC (Y) 2 5.26% CAT (H) → TAT (Y) 2 CGT (R) → TGT (C) 3 total 7 Hydrophilicity → Hydrophobicity ACA (T) → ATA (I) 6 42.11% ACC (T) → ATC (I) 4 ACG (T) → ATG (M) 4 ACT (T) → ATT (I) 8 CGG (R) → TGG (W) 4 TCA (S) → TTA (L) 10 TCC (S) → TTC (F) 1 TCG (S) → TTG (L) 5 TCT (S) → TTT (F) 14 total 56 Hydrophobicity → Hydrophilicity CCA (P) → TCA (S) 5 12.78% CCC (P) → TCC (S) 5 CCG (P) → TCG (S) 1 CCT (P) → TCT (S) 6 total 17 Hydrophobicity → Hydrophobicity CCA (P) → CTA (L) 3 39.10% CCC (P) → CTC (L) 3 CCC (P) → TTC (F) 2 CCG (P) → CTG (L) 1 CCT (P) → CTT (L) 1 CCT (P) → TTT (F) 2 CTC (L) → TTC (F) 5 CTT (L) → TTT (F) 15 GCA (A) → GTA (V) 8 GCC (A) → GTC (V) 3 GCG (A) → GTG (V) 3 GCT (A) → GTT (V) 6 total 52 Hydrophilicity → Termination CGA (R) → TGA (X) 1 0.75% total 1 Repeat sequence analysis Analysis of repeat elements revealed a large number of repeat sequences in the mitochondrial genome. A total of 51 dispersed repeats were detected in the mitochondrial genome of G. tergestina , including 24 forward repeats (F) and 27 palindromic repeats (P) with lengths mainly ranging from 30 to 90 bp; the total length of dispersed repeats was 3,126 bp, accounting for approximately 2.92% of the total mitochondrial genome length, and the length and number of each repeat type are detailed in Table 4 . A total of five tandem repeats were detected in the mitochondrial genome of G. tergestina , with lengths ranging from 16 to 81 bp, among which three tandem repeats showed a similarity higher than 90%, as shown in Table 5 . The distribution of repeat sequences across the genome is illustrated in Fig. 4 . Simple Sequence Repeats (SSRs) are genomic sequences consisting of tandemly repeated 1–6 bp DNA motifs, which are characterized by high genetic variation, strong detection reproducibility, abundant multiple allelism, high genomic abundance and good genome coverage; owing to these advantages, SSRs have become vital resources for developing species-specific polymorphic DNA markers and play irreplaceable roles in plant genetic diversity evaluation, genetic linkage map construction, important trait mapping and molecular-assisted breeding [ 33 – 36 ]. A total of 110 SSRs were identified, including 58 mononucleotides, 39 dinucleotides, 2 trinucleotides, 10 tetranucleotides and 1 pentanucleotide, with mononucleotides being the most abundant type (52.73%) and pentanucleotides the least frequent (0.91%), and the basic characteristics of these SSRs are presented in Table 6 . Table 4 Distribution of Dispersed Repeats Length Dispersed type Number 20–29 P 1 F 0 30–39 P 4 F 2 40–49 P 9 F 5 50–59 P 8 F 3 60–69 P 4 F 5 70–79 P 1 F 2 80–89 P 0 F 5 ≥ 200 P 0 F 2 Table 5 Distribution of Tandem Repeats NO. Size Repeat sequence Percent Matches 1 24 GAATATATATATATATATTCTTTT 100 2 19 CATGACTATCGAAAAGTTCA 83 3 81 CTATCGGATTCGAACCGATAACCCATAGGAACAGATTTTAAGACTGCCG TGTTTACCATTTTCACCAAGCGAGTATGCTCA 92 4 22 GGCTGCAAATGATGAATGTGTG 86 5 16 CGGTAATATATATTAT 100 Table 6 Distribution of SSRs SSR type Motif Count Monomer A/T 53 C/G 5 Dimer AT/AT 38 CG/CG 1 Trimer AAT/ATT 2 Tetramer AAAC/GTTT 1 AAAT/ATTT 6 AATG/ATTC 1 AGAT/ATCT 2 Pentamer AATAT/ATATT 1 Phylogenetic analysis A Neighbor-Joining (NJ) phylogenetic tree was constructed based on the shared mitochondrial CDS sequences of G. tergestina and related taxa (Fig. 5 ). The results showed that Funaria hygrometrica and Physcomitrium patens (Funariaceae) formed a basal sister clade with strong bootstrap support (100). All sampled Grimmiaceae taxa formed a single clade, within which G. tergestina occupied the basal position. Among the remaining Grimmiaceae taxa, Racomitrium elongatum and R. ericoides clustered together with strong support, Codriophorus varius was closely associated with this clade, Codriophorus aciculare and C. laevigatus formed a weakly supported subclade, and Bucklandiella orthotrichacea clustered with Racomitrium emersum. Racomitrium lanuginosum represented another early-diverging lineage within the sampled Grimmiaceae. Comparative mitochondrial genome analysis Global multiple sequence alignment of mitochondrial genomes from closely related taxa, using the G. tergestina mitochondrial genome as the reference, revealed that sequence divergence among the nine mitochondrial genomes was relatively low and mainly concentrated in regions outside the shared functional genes (Fig. 6 ). Several highly variable long regions were identified in the G. tergestina mitochondrial genome, such as ccmFC-rps4, nad6-cox2, and rps11-atp9. Despite these highly variable regions, the mitochondrial genomes of the genus Grimmia exhibited a certain degree of conservation: the overall gene composition was similar (although gene numbers varied considerably), the relative positions of core genes were conserved, and genes related to respiration, electron transport, and translation were relatively conserved. Nucleotide diversity (Pi) reflects the degree of nucleic acid sequence divergence among different species (Fig. 7 ). Five regions (between trnM-CAT and trnK-TTT, rrn26, nad2, nad6, and cob) exhibited relatively high Pi values (> 0.054), indicating high levels of variation. These regions can serve as potential molecular markers for genetic studies of bryophytes. Homology Analysis between Mitochondrial and Chloroplast Genomes The mitochondrial genome of G. tergestina is 17,262 bp smaller than the chloroplast genome (124,153 bp). Compared with the chloroplast genome, mitochondrial genes are relatively sparsely distributed (Fig. 8 ). Based on sequence similarity between the chloroplast and mitochondrial genomes, 38 high-confidence homologous fragments were identified. Among them, 34 were rRNA-derived fragments (89.5%), whereas protein-coding and tRNA-derived fragments accounted for two fragments each. The lengths of the homologous fragments ranged from 30 bp to 258 bp. The identity values were generally above 70%, and all E-values were < 1e-04, indicating that these homologous fragments were non-random and biologically meaningful. The chloroplast rrn16 gene fragments corresponded to the mitochondrial rrn18 region, and the chloroplast rrn23 gene fragments corresponded to the mitochondrial rrn26 region. The chloroplast atpA gene fragment was transferred to the mitochondrial atp1 region, and another fragment was transferred to the mitochondrial nad1 region. The chloroplast trnF-GAA and trnP-UGG gene fragments were transferred to the homologous mitochondrial trnF-GAA and trnP-TGG regions, respectively. Discussion The mitochondrial genome of G. tergestina exhibited a typical circular structure and had a total length of 106,891 bp. In this study, the complete mitochondrial genome sequence of G. tergestina was deposited in the CNSA database, providing a genomic resource for future studies of this species. Analysis of codon usage bias (CUB) provides an important basis for revealing the mechanisms of gene expression regulation and the evolutionary patterns of species. This phenomenon is widespread in the genomes of diverse organisms and shows significant heterogeneity both among and within gene regions [ 37 ]. In plants, nuclear genomes and organellar genomes usually exhibit significantly different codon usage biases. Overall, plant nuclear genomes generally have high GC content, with obvious divergence among different groups: monocot coding sequences tend to frequently use codons ending in C or G, whereas dicots prefer codons ending in A or U [ 38 ]. Previous studies have shown that, compared with the nuclear genome, plant chloroplast and mitochondrial genomes generally exhibit a strong preference for codons ending in A or U. Analyses of diverse plant organellar genomes have further supported this pattern [ 39 – 41 ]. Currently, research on codon usage bias (CUB) in plant mitochondrial genomes remains relatively scarce. Nevertheless, existing findings [ 42 – 44 ] have preliminarily indicated a certain degree of similarity in CUB between mitochondrial and chloroplast genomes, which provides valuable insights for an in-depth exploration of the evolutionary mechanisms underlying plant genomes. Codon composition analysis of G. tergestina in this study showed that the average GC content and GC content at each codon position in its mitochondrial genome were all below 50%, reflecting a strong A/T bias in the overall nucleotide composition, with a preference for A or U at the third codon position. Further analysis revealed that most frequently used codons and optimal codons in this genome also ended in A/U. Preliminary comparative analysis indicated certain differences in mitochondrial codon usage bias among vascular plants, bryophytes, and algae. Bryophytes represented by G. tergestina exhibited distinct codon usage patterns compared with other groups [ 42 , 43 , 45 ]. The major lineages of green plants display both conserved and dynamic characteristics in codon usage bias. Although most species show a general tendency toward A/U-ending codons, the strength of this bias varies significantly among and within lineages. Overall, the preference for A/U-ending codons in bryophytes is significantly lower than that in aquatic charophytes but higher than that in vascular plants, which dominate terrestrial ecosystems. This gradient in codon usage provides molecular evidence supporting the key evolutionary position of bryophytes as a transitional group from aquatic to terrestrial life. Further comparison of mitochondrial genomes among Marchantiophyta, Bryophyta, and Anthocerotophyta revealed lineage-specific differences in codon bias: Marchantiophyta showed the weakest A/U preference at the third codon position, whereas Bryophyta exhibited a more pronounced preference [ 46 ]. The results of the present study also indicate a relatively weak A/U bias in the mitochondrial codon usage of G. tergestina , which contributes to exploring the common genomic features of early-diverging lineages of land plants and identifying broader patterns of codon usage bias. These findings provide comprehensive and in-depth insights for clarifying the phylogenetic relationships and evolutionary history of plant lineages. In this study, only two types of dispersed repeats (forward and palindromic repeats) were identified in the mitochondrial genome of G. tergestina . Similar repeat profiles, in which forward and palindromic repeats predominate, have also been reported in Begonia plastomes [ 39 ]. Most SSRs are composed of adenine (A) and thymine (T) bases. Furthermore, a total of five tandem repeats were detected, among which two showed 100% identity. Comprehensive phylogenetic and comparative analyses indicated that G. tergestina shares high mitochondrial genome similarity with other Grimmiaceae species, suggesting overall conservation within the family. Among the 38 homologous fragments detected between the chloroplast and mitochondrial genomes, most were derived from rRNA regions, whereas only a small proportion corresponded to protein-coding or tRNA-related sequences. This pattern suggests non-random retention of some chloroplast-derived fragments in the mitochondrial genome. Some chloroplast-derived fragments were mapped to annotated mitochondrial regions with related functional categories; however, whether these fragments remain functional requires further experimental validation. The conservation of tRNA-related fragments may reflect sequence-level conservation rather than demonstrated functional transfer. Conclusions In this study, the genome of G. tergestina was sequenced, assembled, and annotated, and the DNA sequences of the annotated genes were analyzed. The complete mitochondrial genome of G. tergestina is 106,891 bp in length, with a GC content of 39.77%. It contains 66 genes, including 39 protein-coding genes (PCGs), 24 tRNA genes, and 3 rRNA genes. Specific analyses were performed on RNA editing sites, codon usage bias, and genomic repetitive sequences. Phylogenetic analysis indicated that G. tergestina occupies a basal position within the sampled Grimmiaceae. This study reports the complete sequence of the mitochondrial genome of G. tergestina and provides its basic characteristics, laying a foundation for further research on the genus Grimmia (bryophytes). Abbreviations CDS: Coding DNA sequence ENC: Effective number of codons GC: Guanine-cytosine NJ: Neighbor-Joining PCGs: Protein-coding genes Pi: Nucleotide diversity RSCU: Relative synonymous codon usage SSRs: Simple sequence repeats tRNA: Transfer RNA rRNA: Ribosomal RNA Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials The data presented in this study are openly available in the China National GeneBank at https://www.cngb.org (accessed on 24 November 2025) under the accession number CNS1408476 . All other data generated or analysed during this study are included in this published article and its supplementary information files, where applicable. Competing interests The authors declare that they have no competing interests. Funding This research was funded by the National Natural Science Foundation of China, grant number 32360296. Authors' contributions Xiaojuan L i: Writing-review & editing, Supervision, Resources, Investigation, Funding acquisition, Methodology, Conceptualization. Hengyu Dai: Writing – review & editing, Visualization, Software, Formal analysis, Resources, Investigation. Shouqiang Li: Resources, Investigation. Huakun Zhou: Supervision. Jiuli Wang: Visualization, Software, Formal analysis. Acknowledgements The authors thank all contributors to sample collection, sequencing, and data analysis. The authors would like to thank Doubao (ByteDance AI) for providing language polishing and technical suggestions during the preparation of this manuscript. The authors are responsible for all content and conclusions of the study. References Ekwealor JTB, Fisher KM. Life under quartz: Hypolithic mosses in the Mojave Desert. PLoS One. 2020;15(7):e0235928. doi:10.1371/journal.pone.0235928. Cao T, Gao Q, Fu X, Lu Y. Diversity of bryophytes and their conservation. 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Adil G, Liu S, Bao X, Mamut R. The chloroplast genome of the Peltigera elisabethae photobiont Chloroidium sp. W5 and its phylogenetic implications. Front Genet. 2025;16:1602048. doi:10.3389/fgene.2025.1602048. Zhou M, Li X. Analysis of synonymous codon usage patterns in different plant mitochondrial genomes. Mol Biol Rep. 2009;36(8):2039-2046. doi:10.1007/s11033-008-9414-1. Xu W, Xing T, Zhao M, Yin X, Xia G, Wang M. Synonymous codon usage bias in plant mitochondrial genes is associated with intron number and mirrors species evolution. PLoS One. 2015;10(6):e0131508. doi:10.1371/journal.pone.0131508. Liu Q, Feng Y, Xue Q. Analysis of factors shaping codon usage in the mitochondrion genome of Oryza sativa. Mitochondrion. 2004;4(4):313-320. doi:10.1016/j.mito.2004.06.003. Wang B, Liu J, Jin L, Feng X, Chen JQ. Complex mutation and weak selection together determined the codon usage bias in bryophyte mitochondrial genomes. J Integr Plant Biol. 2010;52(12):1100-1108. doi:10.1111/j.1744-7909.2010.00998.x. Hu SY, Shi G, Yang CA, Van de Peer Y, Li Z, Xue JY. Comprehensive sampling of mitochondrial genomes substantiates the Neoproterozoic origin of land plants. Plant Commun. 2025;6(11):101497. doi:10.1016/j.xplc.2025.101497. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 08 May, 2026 Reviews received at journal 07 May, 2026 Reviewers agreed at journal 23 Apr, 2026 Reviewers invited by journal 13 Apr, 2026 Editor assigned by journal 13 Apr, 2026 Editor invited by journal 07 Apr, 2026 Submission checks completed at journal 07 Apr, 2026 First submitted to journal 07 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9311791","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":623627859,"identity":"06a3b00d-0591-47b3-9f14-332d32f65030","order_by":0,"name":"Xiaojuan Li","email":"","orcid":"","institution":"Qinghai Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Xiaojuan","middleName":"","lastName":"Li","suffix":""},{"id":623627863,"identity":"aef74033-4621-4956-99d8-8e0d9aa7e1ea","order_by":1,"name":"Hengyu Dai","email":"","orcid":"","institution":"Qinghai Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Hengyu","middleName":"","lastName":"Dai","suffix":""},{"id":623627866,"identity":"e0c5d80c-f72e-4bd6-8679-69962662ae4b","order_by":2,"name":"Shouqiang Li","email":"","orcid":"","institution":"Qinghai Minzu University","correspondingAuthor":false,"prefix":"","firstName":"Shouqiang","middleName":"","lastName":"Li","suffix":""},{"id":623627868,"identity":"493837a6-b2e7-4ba4-b46f-605d514b8a55","order_by":3,"name":"Huakun Zhou","email":"","orcid":"","institution":"Northwest Institute of Plateau Biology","correspondingAuthor":false,"prefix":"","firstName":"Huakun","middleName":"","lastName":"Zhou","suffix":""},{"id":623627869,"identity":"e10173c8-5f74-42de-bc7b-e053d4fceace","order_by":4,"name":"Jiuli Wang","email":"data:image/png;base64,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","orcid":"","institution":"Qinghai Minzu University","correspondingAuthor":true,"prefix":"","firstName":"Jiuli","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-04-03 10:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9311791/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9311791/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107459354,"identity":"b9697c14-59fc-4a83-aed5-8fdab259dfd9","added_by":"auto","created_at":"2026-04-21 16:27:25","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":559411,"visible":true,"origin":"","legend":"\u003cp\u003eMitochondrial genome of \u003cem\u003eGrimmia tergestina\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/7236a2a168264b9dc4b4fecb.jpeg"},{"id":107459346,"identity":"bdf7ec23-c64f-4374-add1-512c89f11c1e","added_by":"auto","created_at":"2026-04-21 16:27:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":76408,"visible":true,"origin":"","legend":"\u003cp\u003eRelative synonymous codon usage (RSCU) in the mitochondrial genome of \u003cem\u003eGrimmia tergestina.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/a59858ea48f71c84f9c96e04.png"},{"id":107868258,"identity":"cc451d16-d5e5-4c7c-b78e-e44acdb69997","added_by":"auto","created_at":"2026-04-27 07:09:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73875,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of RNA editing sites. The x-axis represents gene names, and the y-axis represents the number of RNA editing events.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/e7090356484a479c5b5cf004.png"},{"id":107488317,"identity":"a8cd1572-e873-4bb4-9df5-b27bc5ce28ca","added_by":"auto","created_at":"2026-04-22 02:44:15","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":202584,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of repeat sequences in the \u003cem\u003eGrimmia tergestina \u003c/em\u003emitochondrial genome. The outermost circle represents SSRs, the middle circle represents tandem repeats, and the innermost circle represents dispersed repeats.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/1dbbcd2402784ea237174bcb.png"},{"id":107459348,"identity":"5e7139bc-264f-4889-8b67-83e1890bea0a","added_by":"auto","created_at":"2026-04-21 16:27:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":33409,"visible":true,"origin":"","legend":"\u003cp\u003ePhylogenetic relationships of Grimmia tergestina and related taxa based on shared mitochondrial CDSs.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/568f6d06d050edd42d261089.png"},{"id":107490347,"identity":"b11489d2-9b49-4b2f-9ee5-c4def184bd7b","added_by":"auto","created_at":"2026-04-22 02:51:48","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":4163431,"visible":true,"origin":"","legend":"\u003cp\u003eGlobal multiple sequence alignment of mitochondrial genomes of \u003cem\u003eGrimmia tergestina\u003c/em\u003e and its closely related taxa.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/214c3a40c4b4046f69d05145.png"},{"id":107459350,"identity":"933dc492-e0cc-44e6-b4f3-f8881483ea6f","added_by":"auto","created_at":"2026-04-21 16:27:24","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":185088,"visible":true,"origin":"","legend":"\u003cp\u003eNucleotide sequence divergence of \u003cem\u003eGrimmia tergestina\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/3861fd83738a6cf31d6416c2.png"},{"id":107489340,"identity":"5c7dd7d0-4a9d-4cd8-b2e5-6d75fcd607f8","added_by":"auto","created_at":"2026-04-22 02:47:25","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":183162,"visible":true,"origin":"","legend":"\u003cp\u003eFragments transferred from chloroplast to mitochondrion in \u003cem\u003eGrimmia tergestina\u003c/em\u003e.\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/e3e36167f12b2ea6f8ec2dfc.png"},{"id":108006343,"identity":"17898945-1747-44ba-9b24-b1097dc277ae","added_by":"auto","created_at":"2026-04-28 12:55:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5742984,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9311791/v1/963a9006-850b-482c-b4e8-bb21d03142ad.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comprehensive Analysis of the Mitochondrial Genome of Grimmia tergestina: Codon Usage Bias, RNA Editing, and Organelle DNA Transfer","fulltext":[{"header":"Background","content":"\u003cp\u003eBryophytes represent the second most species-rich group of land plants after angiosperms and are widely distributed in diverse habitats, including deserts, alpine ecosystems, and high-elevation regions. Their unique structural and physiological characteristics, such as tolerance to drought, cold, and nutrient-poor conditions, enable them to play crucial ecological roles in global ecosystems [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Species within the family Grimmiaceae are particularly adapted to semi-arid environments and are commonly found on exposed rocks or cliff surfaces in mountainous regions. Due to their distinctive morphological features and ecological specialization, these plants can provide important insights into plant floristic evolution and species diversification [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. \u003cem\u003eGrimmia tergestina\u003c/em\u003e Tomm. ex Bruch \u0026amp; Schimp., a perennial xerophytic moss species belonging to the genus Grimmia Hedw. within the family Grimmiaceae, commonly inhabits exposed rocky substrates in arid and semiarid environments, particularly in alpine or high-altitude regions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eMitochondria are essential cellular organelles responsible for respiration, energy production, and numerous metabolic processes. Similar to chloroplasts, plant mitochondria possess their own genomes, which are thought to originate from ancient endosymbiotic events [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePlant mitochondrial genomes exhibit several distinctive characteristics, including large genome sizes, complex structural organization, extensive recombination, and frequent intracellular gene transfer events [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These features make mitochondrial genomes important resources for studying genome evolution, organellar interactions, and phylogenetic relationships among plant lineages.\u003c/p\u003e \u003cp\u003eChloroplast and mitochondrial genomes within the same species exhibit significant differences in genomic organization, sequence length, gene composition, and expression patterns. These differences are largely influenced by gene transfer events and functional replacement by nuclear genes. Mutation rates and structural variation patterns also differ between these genomes. For instance, the evolutionary rate of chloroplast genomes is approximately half that of nuclear genomes, whereas plant mitochondrial genomes evolve even more slowly [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Such characteristics have important implications for understanding evolutionary processes and reconstructing phylogenetic relationships. These variations may influence phylogenetic inference based on organellar genome data [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In addition, plant mitochondrial genomes often contain repetitive sequences and exhibit extensive RNA editing, both of which contribute to post-transcriptional regulation and protein diversity [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCodon usage bias is the preferential or non-random use of synonymous codons, a ubiquitous phenomenon observed in bacteria, plants, and animals [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Analysis of codon usage bias provides valuable insights into gene expression regulation, gene function prediction, genetic variation among species, and the mechanisms underlying molecular evolution [\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Previous studies have shown that plant organellar genomes generally exhibit a preference for codons ending in A or U, reflecting the nucleotide composition bias of these genomes [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, comprehensive investigations of codon usage bias in bryophyte mitochondrial genomes remain scarce.\u003c/p\u003e \u003cp\u003eFurthermore, extensive gene transfer occurs between chloroplasts and mitochondria. This process involves not only intragenomic recombination within organelles, but also inter-organellar DNA transfer and gene transfer from organelles to the nucleus, known as \u0026ldquo;nuclear-organellar gene flow\u0026rdquo;. This phenomenon reflects the dynamic and continuous nature of life evolution and provides insights into how organisms adapt to environmental changes and optimize their physiological functions [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Although chloroplast-to-mitochondrion DNA transfer has been reported in several plant species, the extent and functional implications of such transfers in bryophytes remain poorly understood.\u003c/p\u003e \u003cp\u003eThe genus Grimmia (Grimmiaceae) comprises numerous species adapted to extreme environmental conditions, particularly in alpine and arid habitats. Despite their ecological significance, genomic resources for many Grimmia species remain limited. In particular, mitochondrial genomic data for this genus are still lacking, which hinders our understanding of mitochondrial genome evolution and organellar interactions in bryophytes.\u003c/p\u003e \u003cp\u003eIn this study, we assembled and characterized the complete mitochondrial genome of G. tergestina. We conducted comprehensive analyses of genome structure, gene content, codon usage bias, RNA editing sites, repetitive sequences, and phylogenetic relationships. In addition, we investigated homologous fragments between mitochondrial and chloroplast genomes to explore potential intracellular DNA transfer events. The results provide new insights into mitochondrial genome evolution and organelle genome interactions in bryophytes and contribute to a deeper understanding of the evolutionary mechanisms underlying early land plant diversification.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSample collection and sequencing\u003c/h2\u003e \u003cp\u003eWild samples of G. tergestina were collected in October 2024 from exposed alpine rocks along the southern bank of the Yellow River in Huangheqing National Wetland Park, Guide County, Qinghai Province, China (36.051258\u0026deg;N, 101.301659\u0026deg;E). Field sampling was conducted in accordance with local legislation, and no specific permission was required for the collection of this bryophyte material from the sampling site. The collected samples were formally identified as G. tergestina by Prof. Xueliang Bai, Inner Mongolia Normal University, China. A voucher specimen was deposited in the Sample Room of the Qinghai Provincial Biotechnology and Analytical Test Key Laboratory, Qinghai Minzu University, Xining, China, under voucher number HHQ2024001.\u003c/p\u003e \u003cp\u003eImmediately after collection, samples were rapidly frozen in liquid nitrogen and transported on dry ice to Nanjing Jisi Huiyuan Biotechnology Co., Ltd. for organelle genome sequencing. Mitochondrial genomes were sequenced using the Illumina NovaSeq 6000 platform with paired-end sequencing (PE150 mode). Raw sequencing reads were quality filtered using Trimmomatic v0.39 with a Phred score threshold\u0026thinsp;\u0026ge;\u0026thinsp;30. High-quality reads were subsequently assembled using SPAdes v3.15.3. The circularity of the assembled mitochondrial genome was verified using Bandage v0.8.1 to ensure sequence completeness [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGenome assembly, annotation and visualization\u003c/h3\u003e\n\u003cp\u003eThe complete mitochondrial genome of G. tergestina is 106,891 bp in length and has been deposited in the CNSA database under accession number CNS1408476. The genome contains 39 coding DNA sequences (CDS). Initial genome annotation was performed using the DOGMA program, followed by manual correction of start and stop codons as well as intron boundaries using Geneious v9.0.2 [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. For codon usage bias analysis, coding sequences (CDS) longer than 300 bp were selected according to the following criteria: an ATG start codon, a valid stop codon, absence of internal stop codons, and no interference from repetitive sequences. The circular mitochondrial genome map was generated using the online tool OGDRAW.\u003c/p\u003e\n\u003ch3\u003eCodon usage bias analysis\u003c/h3\u003e\n\u003cp\u003eCodon usage parameters were calculated using CodonW v1.4.2. The following indices were used: CAI (Codon Adaptation Index), which was used to evaluate gene expression level and ranges from 0 to 1, with higher values indicating greater expression potential; RSCU (Relative Synonymous Codon Usage), which indicates codon preference when the value is greater than 1; and ENC (Effective Number of Codons), which measures codon bias and ranges from 20 (strong bias) to 61 (no bias).\u003c/p\u003e\n\u003ch3\u003eIdentification of optimal codons\u003c/h3\u003e\n\u003cp\u003eWhen the RSCU value equals 1, codon usage is considered unbiased. Codons with RSCU values greater than 1 are defined as high-frequency codons, whereas those with values less than 1 are considered low-frequency codons. Optimal codons were identified based on RSCU values combined with codon usage patterns [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003ePhylogenetic analysis\u003c/h3\u003e\n\u003cp\u003eComplete mitochondrial genome sequences of nine species from Grimmiaceae and two species from Funariaceae were downloaded from the NCBI database for phylogenetic analysis. Sequence alignment was performed using MAFFT version 7.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mafft.cbrc.jp/alignment/server/\u003c/span\u003e\u003cspan address=\"https://mafft.cbrc.jp/alignment/server/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. A phylogenetic tree was constructed using the Neighbor-Joining (NJ) method implemented in MEGA7.0 with 1000 bootstrap replicates [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. The final phylogenetic tree was visualized using OGDRAW (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://chlorobox.mpimp-golm.mpg.de/OGDraw.html\u003c/span\u003e\u003cspan address=\"https://chlorobox.mpimp-golm.mpg.de/OGDraw.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTaxa included in phylogenetic analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubclass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOrder\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecies\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAccession No.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGenome Size\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRacomitrium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eRacomitrium elongatum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKP687246.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106746 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRacomitrium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eRacomitrium ericoides\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKP233863.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106727 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCodriophorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCodriophorus varius\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKP687247.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106358 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCodriophorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCodriophorus aciculare\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKP453983.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106818 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCodriophorus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eCodriophorus laevigatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKM506905.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106809 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBucklandiella\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eBucklandiella orthotrichacea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKP742835.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107215 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRacomitrium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eRacomitrium emersum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKP742836.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e107186 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eRacomitrium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eRacomitrium lanuginosum\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKU050083.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106795 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDicranidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGrimmiales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGrimmiaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eGrimmia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eGrimmia tergestina\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCNS1408476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e106,891 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBryidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFunariales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFunariaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eFunaria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eFunaria hygrometrica\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKC784959.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e109586 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFunariidae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFunariales\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFunariaceae\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePhyscomitrium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ePhyscomitrium patens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eKY126309.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e105340 bp\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eRepeat sequence analysis\u003c/h2\u003e \u003cp\u003eDispersed repeats in the mitochondrial genome were identified using the online tool REPuter with the following parameters: Hamming distance\u0026thinsp;=\u0026thinsp;3 and minimum repeat size of 20 bp [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Four types of repeats were considered: forward (F), reverse (R), complement (C), and palindromic (P) repeats. Simple sequence repeats (SSRs) were identified using MISA with the following minimum repeat thresholds [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]: mononucleotide repeats\u0026thinsp;\u0026ge;\u0026thinsp;10, dinucleotide repeats\u0026thinsp;\u0026ge;\u0026thinsp;5, trinucleotide repeats\u0026thinsp;\u0026ge;\u0026thinsp;4, and tetra-, penta-, and hexanucleotide repeats\u0026thinsp;\u0026ge;\u0026thinsp;3\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparative Analysis of Mitochondrial Genome Sequences of Grimmia tergestina and Its Related Taxa\u003c/h3\u003e\n\u003cp\u003eGenome similarity among related species was analyzed using the LAGAN mode in mVISTA, with the mitochondrial genome of G. tergestina used as the reference [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eNucleotide diversity analysis\u003c/h3\u003e\n\u003cp\u003eMultiple sequence alignment of mitochondrial genome sequences was performed using MAFFT 7.409 in a Linux environment. The aligned sequences were imported into DnaSP v6.12.03 for nucleotide diversity (Pi) analysis and visualization.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of homologous sequences between mitochondrial and chloroplast genomes\u003c/h2\u003e \u003cp\u003eHomologous fragments between mitochondrial and chloroplast genomes were identified using BLAST implemented in TBtools. The filtering criteria were as follows: sequence identity\u0026thinsp;\u0026ge;\u0026thinsp;70%, E-value\u0026thinsp;\u0026le;\u0026thinsp;1e-4, and alignment length\u0026thinsp;\u0026ge;\u0026thinsp;30 bp. Identified homologous fragments were visualized using Circos (v0.69-5).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eMitochondrial genome structure and gene composition\u003c/h2\u003e \u003cp\u003eThe mitochondrial genome of G. tergestina forms a typical circular molecule with a total length of 106,891 bp (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The overall GC content of the genome is 39.77%. Among different gene categories, the GC content of protein-coding genes (PCGs) (35.26%) was lower than that of tRNA genes (46.36%) and rRNA genes (47.24%).\u003c/p\u003e \u003cp\u003eA total of 66 genes were annotated in the mitochondrial genome, including 39 protein-coding genes (PCGs), 24 tRNA genes, and 3 rRNA genes (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Among these genes, 15 genes contained introns, including atp1, atp6, atp9, ccmFC, cob, cox1, cox2, cox3, nad1, nad2, nad4, nad5, nad7, nad9, and sdh3, comprising 27 introns in total. Genes encoding NADH dehydrogenase subunits contained the largest number of introns (11 introns). Notably, three copies of the trnM-CAT gene were identified in the mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e, indicating a unique gene copy structure.Among the protein-coding genes, the most common start codon was ATG, and the most frequently observed stop codon was TAA.\u003c/p\u003e \u003cp\u003eThe 24 tRNA genes encode 18 of the 20 standard amino acids, including alanine (Ala), cysteine (Cys), aspartic acid (Asp), glutamic acid (Glu), phenylalanine (Phe), histidine (His), lysine (Lys), leucine (Leu), methionine (Met), proline (Pro), glutamine (Gln), arginine (Arg), serine (Ser), threonine (Thr), valine (Val), tryptophan (Trp), tyrosine (Tyr), and glycine (Gly).\u003c/p\u003e \u003cp\u003eSome amino acids were encoded by two tRNA genes with different anticodons, such as trnG-GCC / trnG-TCC and trnR-ACG / trnR-TCT. Additionally, certain tRNA genes showed gene duplication, such as trnF-GAA and trnG-GCC, while trnM-CAT occurred in three copies, which may reflect lineage-specific copy-number variation or genomic organization.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of the Mitochondrial Genome of \u003cem\u003eGrimmia tergestina\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup of genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStart codon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStop codon\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAmino acid\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eATP synthase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eatp\u003c/em\u003e1*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eatp\u003c/em\u003e4*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e552\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e184\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eatp\u003c/em\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eatp\u003c/em\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e525\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eatp\u003c/em\u003e9***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eCytochrome c biogenesis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eccm\u003c/em\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e528\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e176\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eccm\u003c/em\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eccm\u003c/em\u003eFC*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e463\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eccm\u003c/em\u003eFn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e610\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUbichinol cytochrome c reductase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecob\u003c/em\u003e*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCytochrome c oxidase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecox\u003c/em\u003e1****\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e523\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecox\u003c/em\u003e2***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ecox\u003c/em\u003e3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTransport membrane protein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003emtt\u003c/em\u003eB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eACG (ATG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eNADH dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e1**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e329\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e2*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e490\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e496\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e4L*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e303\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e5***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e677\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e7**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e394\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003enad\u003c/em\u003e9*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGTG (not determined/transl_except)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eRibosomal proteins (LSU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpl\u003c/em\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e540\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpl\u003c/em\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1395\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e465\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpl\u003c/em\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e187\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erpl\u003c/em\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e306\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003eRibosomal proteins (SSU)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e810\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e282\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1617\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e539\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e588\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003erps\u003c/em\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e720\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSuccinate dehydrogenase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003esdh\u003c/em\u003e3*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e396\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e132\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003esdh\u003c/em\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eATG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eRibosomal RNAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003errn\u003c/em\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003errn\u003c/em\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3356\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003errn\u003c/em\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"21\" rowspan=\"22\"\u003e \u003cp\u003eTransfer RNAs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eA-TGC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eC-GCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eD-GTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eE-TTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eF-GAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eG-GCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eG-TCC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eH-GTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eK-TTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eL-CAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eL-TAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eL-TAG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eM-CAT (3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(74, 73, 73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eP-TGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eQ-TTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eR-ACG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eR-TCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eS-TGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eT-GGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eV-TAC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eW-CCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003etrn\u003c/em\u003eY-GTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eCodon usage bias\u003c/h2\u003e \u003cp\u003eA total of 30 codons exhibited RSCU values greater than 1, indicating preferential usage. Among these, 29 high-frequency codons ended with A or U, accounting for 96.7% (13 codons ended with A, accounting for 43.3%, and 16 codons ended with U, accounting for 53.3%), suggesting a strong A/U preference in synonymous codon selection. The most frequently used optimal codon was UUA, which encodes leucine (Leu). These results indicate that the mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e exhibits a pronounced A/U-ending codon preference, a pattern commonly observed in plant mitochondrial genomes and likely influenced by mutational pressure and translational selection. The schematic diagram of codon usage bias is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe boxes below represent all codons encoding each amino acid, and the height of the bars above indicates the sum of RSCU values for all codons.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eRNA editing site prediction\u003c/h2\u003e \u003cp\u003eA total of 133 RNA editing sites were predicted in 34 of the 39 protein-coding genes, and all of them were C-to-T editing events (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The number of predicted editing sites per gene ranged from 1 to 13. Among all genes, rps3 contained the highest number of predicted editing sites (13), followed by ccmFC and rpl2 (10 each), ccmFn (9), atp8 (8), mttB (7), and sdh3 (6). Most of the remaining genes contained only 1\u0026ndash;5 editing sites, whereas no predicted editing sites were detected in five protein-coding genes. The RNA editing events were classified into five categories according to the hydrophilicity of the amino acid changes (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Among them, hydrophilic-to-hydrophobic conversions were the most frequent (42.11%), followed by hydrophobic-to-hydrophobic conversions (39.10%), hydrophobic-to-hydrophilic conversions (12.78%), and hydrophilic-to-hydrophilic conversions (5.26%). Only one predicted editing event (0.75%) generated a premature termination codon. A total of 29 codon transition types were identified, among which CTT (L)\u0026rarr;TTT (F) was the most frequent, occurring 15 times. RNA editing mainly affected the first and second codon positions, and a small number of codon transitions involved simultaneous changes at both positions. Overall, RNA editing resulted in the greatest increase in phenylalanine, including 20 conversions from leucine, 15 from serine, and 4 from proline.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of RNA Editing Sites\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRNA-editing\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrophilicity \u0026rarr; Hydrophilicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAC (H) \u0026rarr; TAC (Y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5.26%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAT (H) \u0026rarr; TAT (Y)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGT (R) \u0026rarr; TGT (C)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrophilicity \u0026rarr; Hydrophobicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACA (T) \u0026rarr; ATA (I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACC (T) \u0026rarr; ATC (I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACG (T) \u0026rarr; ATG (M)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eACT (T) \u0026rarr; ATT (I)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGG (R) \u0026rarr; TGG (W)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCA (S) \u0026rarr; TTA (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCC (S) \u0026rarr; TTC (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCG (S) \u0026rarr; TTG (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTCT (S) \u0026rarr; TTT (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrophobicity \u0026rarr; Hydrophilicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCA (P) \u0026rarr; TCA (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e12.78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCC (P) \u0026rarr; TCC (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCG (P) \u0026rarr; TCG (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCT (P) \u0026rarr; TCT (S)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrophobicity \u0026rarr; Hydrophobicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCA (P) \u0026rarr; CTA (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e39.10%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCC (P) \u0026rarr; CTC (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCC (P) \u0026rarr; TTC (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCG (P) \u0026rarr; CTG (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCT (P) \u0026rarr; CTT (L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCCT (P) \u0026rarr; TTT (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTC (L) \u0026rarr; TTC (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCTT (L) \u0026rarr; TTT (F)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCA (A) \u0026rarr; GTA (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCC (A) \u0026rarr; GTC (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCG (A) \u0026rarr; GTG (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCT (A) \u0026rarr; GTT (V)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHydrophilicity \u0026rarr; Termination\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGA (R) \u0026rarr; TGA (X)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.75%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003etotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eRepeat sequence analysis\u003c/h2\u003e \u003cp\u003eAnalysis of repeat elements revealed a large number of repeat sequences in the mitochondrial genome. A total of 51 dispersed repeats were detected in the mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e, including 24 forward repeats (F) and 27 palindromic repeats (P) with lengths mainly ranging from 30 to 90 bp; the total length of dispersed repeats was 3,126 bp, accounting for approximately 2.92% of the total mitochondrial genome length, and the length and number of each repeat type are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. A total of five tandem repeats were detected in the mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e, with lengths ranging from 16 to 81 bp, among which three tandem repeats showed a similarity higher than 90%, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The distribution of repeat sequences across the genome is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eSimple Sequence Repeats (SSRs) are genomic sequences consisting of tandemly repeated 1\u0026ndash;6 bp DNA motifs, which are characterized by high genetic variation, strong detection reproducibility, abundant multiple allelism, high genomic abundance and good genome coverage; owing to these advantages, SSRs have become vital resources for developing species-specific polymorphic DNA markers and play irreplaceable roles in plant genetic diversity evaluation, genetic linkage map construction, important trait mapping and molecular-assisted breeding [\u003cspan additionalcitationids=\"CR34 CR35\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. A total of 110 SSRs were identified, including 58 mononucleotides, 39 dinucleotides, 2 trinucleotides, 10 tetranucleotides and 1 pentanucleotide, with mononucleotides being the most abundant type (52.73%) and pentanucleotides the least frequent (0.91%), and the basic characteristics of these SSRs are presented in Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Dispersed Repeats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDispersed type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60\u0026ndash;69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e70\u0026ndash;79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e80\u0026ndash;89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of Tandem Repeats\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNO.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSize\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRepeat sequence\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent Matches\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGAATATATATATATATATTCTTTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCATGACTATCGAAAAGTTCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCTATCGGATTCGAACCGATAACCCATAGGAACAGATTTTAAGACTGCCG\u003c/p\u003e \u003cp\u003eTGTTTACCATTTTCACCAAGCGAGTATGCTCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGCTGCAAATGATGAATGTGTG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCGGTAATATATATTAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of SSRs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSSR type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMotif\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCount\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonomer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eA/T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC/G\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAT/AT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCG/CG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrimer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAT/ATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTetramer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAAC/GTTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAAT/ATTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAATG/ATTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAGAT/ATCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePentamer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAATAT/ATATT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic analysis\u003c/h2\u003e \u003cp\u003eA Neighbor-Joining (NJ) phylogenetic tree was constructed based on the shared mitochondrial CDS sequences of \u003cem\u003eG. tergestina\u003c/em\u003e and related taxa (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). The results showed that Funaria hygrometrica and Physcomitrium patens (Funariaceae) formed a basal sister clade with strong bootstrap support (100). All sampled Grimmiaceae taxa formed a single clade, within which \u003cem\u003eG. tergestina\u003c/em\u003e occupied the basal position. Among the remaining Grimmiaceae taxa, Racomitrium elongatum and R. ericoides clustered together with strong support, Codriophorus varius was closely associated with this clade, Codriophorus aciculare and C. laevigatus formed a weakly supported subclade, and Bucklandiella orthotrichacea clustered with Racomitrium emersum. Racomitrium lanuginosum represented another early-diverging lineage within the sampled Grimmiaceae.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eComparative mitochondrial genome analysis\u003c/h2\u003e \u003cp\u003eGlobal multiple sequence alignment of mitochondrial genomes from closely related taxa, using the \u003cem\u003eG. tergestina\u003c/em\u003e mitochondrial genome as the reference, revealed that sequence divergence among the nine mitochondrial genomes was relatively low and mainly concentrated in regions outside the shared functional genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). Several highly variable long regions were identified in the \u003cem\u003eG. tergestina\u003c/em\u003e mitochondrial genome, such as ccmFC-rps4, nad6-cox2, and rps11-atp9. Despite these highly variable regions, the mitochondrial genomes of the genus Grimmia exhibited a certain degree of conservation: the overall gene composition was similar (although gene numbers varied considerably), the relative positions of core genes were conserved, and genes related to respiration, electron transport, and translation were relatively conserved.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNucleotide diversity (Pi) reflects the degree of nucleic acid sequence divergence among different species (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e). Five regions (between trnM-CAT and trnK-TTT, rrn26, nad2, nad6, and cob) exhibited relatively high Pi values (\u0026gt;\u0026thinsp;0.054), indicating high levels of variation. These regions can serve as potential molecular markers for genetic studies of bryophytes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eHomology Analysis between Mitochondrial and Chloroplast Genomes\u003c/h2\u003e \u003cp\u003eThe mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e is 17,262 bp smaller than the chloroplast genome (124,153 bp). Compared with the chloroplast genome, mitochondrial genes are relatively sparsely distributed (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e). Based on sequence similarity between the chloroplast and mitochondrial genomes, 38 high-confidence homologous fragments were identified. Among them, 34 were rRNA-derived fragments (89.5%), whereas protein-coding and tRNA-derived fragments accounted for two fragments each. The lengths of the homologous fragments ranged from 30 bp to 258 bp. The identity values were generally above 70%, and all E-values were \u0026lt;\u0026thinsp;1e-04, indicating that these homologous fragments were non-random and biologically meaningful. The chloroplast rrn16 gene fragments corresponded to the mitochondrial rrn18 region, and the chloroplast rrn23 gene fragments corresponded to the mitochondrial rrn26 region. The chloroplast atpA gene fragment was transferred to the mitochondrial atp1 region, and another fragment was transferred to the mitochondrial nad1 region. The chloroplast trnF-GAA and trnP-UGG gene fragments were transferred to the homologous mitochondrial trnF-GAA and trnP-TGG regions, respectively.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e exhibited a typical circular structure and had a total length of 106,891 bp. In this study, the complete mitochondrial genome sequence of \u003cem\u003eG. tergestina\u003c/em\u003e was deposited in the CNSA database, providing a genomic resource for future studies of this species.\u003c/p\u003e \u003cp\u003eAnalysis of codon usage bias (CUB) provides an important basis for revealing the mechanisms of gene expression regulation and the evolutionary patterns of species. This phenomenon is widespread in the genomes of diverse organisms and shows significant heterogeneity both among and within gene regions [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. In plants, nuclear genomes and organellar genomes usually exhibit significantly different codon usage biases. Overall, plant nuclear genomes generally have high GC content, with obvious divergence among different groups: monocot coding sequences tend to frequently use codons ending in C or G, whereas dicots prefer codons ending in A or U [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Previous studies have shown that, compared with the nuclear genome, plant chloroplast and mitochondrial genomes generally exhibit a strong preference for codons ending in A or U. Analyses of diverse plant organellar genomes have further supported this pattern [\u003cspan additionalcitationids=\"CR40\" citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Currently, research on codon usage bias (CUB) in plant mitochondrial genomes remains relatively scarce. Nevertheless, existing findings [\u003cspan additionalcitationids=\"CR43\" citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] have preliminarily indicated a certain degree of similarity in CUB between mitochondrial and chloroplast genomes, which provides valuable insights for an in-depth exploration of the evolutionary mechanisms underlying plant genomes.\u003c/p\u003e \u003cp\u003eCodon composition analysis of \u003cem\u003eG. tergestina\u003c/em\u003e in this study showed that the average GC content and GC content at each codon position in its mitochondrial genome were all below 50%, reflecting a strong A/T bias in the overall nucleotide composition, with a preference for A or U at the third codon position. Further analysis revealed that most frequently used codons and optimal codons in this genome also ended in A/U. Preliminary comparative analysis indicated certain differences in mitochondrial codon usage bias among vascular plants, bryophytes, and algae. Bryophytes represented by \u003cem\u003eG. tergestina\u003c/em\u003e exhibited distinct codon usage patterns compared with other groups [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. The major lineages of green plants display both conserved and dynamic characteristics in codon usage bias. Although most species show a general tendency toward A/U-ending codons, the strength of this bias varies significantly among and within lineages. Overall, the preference for A/U-ending codons in bryophytes is significantly lower than that in aquatic charophytes but higher than that in vascular plants, which dominate terrestrial ecosystems. This gradient in codon usage provides molecular evidence supporting the key evolutionary position of bryophytes as a transitional group from aquatic to terrestrial life. Further comparison of mitochondrial genomes among Marchantiophyta, Bryophyta, and Anthocerotophyta revealed lineage-specific differences in codon bias: Marchantiophyta showed the weakest A/U preference at the third codon position, whereas Bryophyta exhibited a more pronounced preference [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The results of the present study also indicate a relatively weak A/U bias in the mitochondrial codon usage of \u003cem\u003eG. tergestina\u003c/em\u003e, which contributes to exploring the common genomic features of early-diverging lineages of land plants and identifying broader patterns of codon usage bias. These findings provide comprehensive and in-depth insights for clarifying the phylogenetic relationships and evolutionary history of plant lineages.\u003c/p\u003e \u003cp\u003eIn this study, only two types of dispersed repeats (forward and palindromic repeats) were identified in the mitochondrial genome of \u003cem\u003eG. tergestina\u003c/em\u003e. Similar repeat profiles, in which forward and palindromic repeats predominate, have also been reported in Begonia plastomes [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Most SSRs are composed of adenine (A) and thymine (T) bases. Furthermore, a total of five tandem repeats were detected, among which two showed 100% identity.\u003c/p\u003e \u003cp\u003eComprehensive phylogenetic and comparative analyses indicated that \u003cem\u003eG. tergestina\u003c/em\u003e shares high mitochondrial genome similarity with other Grimmiaceae species, suggesting overall conservation within the family. Among the 38 homologous fragments detected between the chloroplast and mitochondrial genomes, most were derived from rRNA regions, whereas only a small proportion corresponded to protein-coding or tRNA-related sequences. This pattern suggests non-random retention of some chloroplast-derived fragments in the mitochondrial genome. Some chloroplast-derived fragments were mapped to annotated mitochondrial regions with related functional categories; however, whether these fragments remain functional requires further experimental validation. The conservation of tRNA-related fragments may reflect sequence-level conservation rather than demonstrated functional transfer.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003e \u003cb\u003eIn this study, the genome of\u003c/b\u003e \u003cb\u003eG. tergestina\u003c/b\u003e \u003cb\u003ewas sequenced, assembled, and annotated, and the DNA sequences of the annotated genes were analyzed. The complete mitochondrial genome of\u003c/b\u003e \u003cb\u003eG. tergestina\u003c/b\u003e \u003cb\u003eis 106,891 bp in length, with a GC content of 39.77%. It contains 66 genes, including 39 protein-coding genes (PCGs), 24 tRNA genes, and 3 rRNA genes. Specific analyses were performed on RNA editing sites, codon usage bias, and genomic repetitive sequences. Phylogenetic analysis indicated that\u003c/b\u003e \u003cb\u003eG. tergestina\u003c/b\u003e \u003cb\u003eoccupies a basal position within the sampled Grimmiaceae. This study reports the complete sequence of the mitochondrial genome of\u003c/b\u003e \u003cb\u003eG. tergestina\u003c/b\u003e \u003cb\u003eand provides its basic characteristics, laying a foundation for further research on the genus Grimmia (bryophytes).\u003c/b\u003e\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCDS: Coding DNA sequence\u003cbr\u003e\u0026nbsp;ENC: Effective number of codons\u003cbr\u003e\u0026nbsp;GC: Guanine-cytosine\u003cbr\u003e\u0026nbsp;NJ: Neighbor-Joining\u003cbr\u003e\u0026nbsp;PCGs: Protein-coding genes\u003cbr\u003e\u0026nbsp;Pi: Nucleotide diversity\u003cbr\u003e\u0026nbsp;RSCU: Relative synonymous codon usage\u003cbr\u003e\u0026nbsp;SSRs: Simple sequence repeats\u003cbr\u003e\u0026nbsp;tRNA: Transfer RNA\u003cbr\u003e\u0026nbsp;rRNA: Ribosomal RNA\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe data presented in this study are openly available in the China National GeneBank at https://www.cngb.org (accessed on 24 November 2025) under the accession number \u003cstrong\u003eCNS1408476\u003c/strong\u003e. All other data generated or analysed during this study are included in this published article and its supplementary information files, where applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research was funded by the National Natural Science Foundation of China, grant number 32360296.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003e\u003cstrong\u003eXiaojuan L\u003c/strong\u003e\u003cstrong\u003ei:\u003c/strong\u003e Writing-review \u0026amp; editing, Supervision, Resources, Investigation, Funding acquisition, Methodology, Conceptualization.\u0026nbsp;\u003cstrong\u003eHengyu Dai:\u003c/strong\u003e Writing \u0026ndash; review \u0026amp; editing, Visualization, Software, Formal analysis, Resources, Investigation. \u003cstrong\u003eShouqiang Li:\u003c/strong\u003e Resources, Investigation.\u0026nbsp;\u003cstrong\u003eHuakun Zhou:\u003c/strong\u003e Supervision. \u003cstrong\u003eJiuli Wang:\u003c/strong\u003e Visualization, Software, Formal analysis.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eThe authors thank all contributors to sample collection, sequencing, and data analysis. The authors would like to thank Doubao (ByteDance AI) for providing language polishing and technical suggestions during the preparation of this manuscript. The authors are responsible for all content and conclusions of the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEkwealor JTB, Fisher KM. Life under quartz: Hypolithic mosses in the Mojave Desert. PLoS One. 2020;15(7):e0235928. doi:10.1371/journal.pone.0235928.\u003c/li\u003e\n\u003cli\u003eCao T, Gao Q, Fu X, Lu Y. Diversity of bryophytes and their conservation. Chin J Ecol. 1997;16(2):47-52. doi:10.13292/j.1000-4890.1997.0026.\u003c/li\u003e\n\u003cli\u003eIgnatov MS, Ignatova EA, Ivanova EI, Isakova VG, Ivanov OV, Seregin AP. MHA Herbarium: Collections of mosses from Yana-Indigirka Region, Yakutia, Russia. Biodivers Data J. 2022;10:e77341. doi:10.3897/BDJ.10.e77341.\u003c/li\u003e\n\u003cli\u003eMcLean JR, Cohn GL, Brandt IK, Simpson MV. 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Plant Commun. 2025;6(11):101497. doi:10.1016/j.xplc.2025.101497.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Grimmia tergestina, mitochondrial genome, codon usage bias, RNA editing, repetitive sequences, organelle genome evolution, bryophytes","lastPublishedDoi":"10.21203/rs.3.rs-9311791/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9311791/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003e \u003cem\u003eGrimmia tergestina\u003c/em\u003e Tomm. ex Bruch \u0026amp; Schimp. is a perennial xerophytic moss adapted to exposed rocky habitats, yet its mitochondrial genome architecture and associated post-transcriptional and inter-organellar evolutionary features remain poorly characterized. This study aimed to assemble and characterize the complete mitochondrial genome of \u003cem\u003eGrimmia tergestina\u003c/em\u003e and to examine its codon usage bias, RNA editing, repetitive sequences, phylogenetic position, and homologous sequence transfer between mitochondrial and chloroplast genomes.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe complete mitochondrial genome of \u003cem\u003eGrimmia tergestina\u003c/em\u003e is a circular molecule of 106,891 bp with a GC content of 39.77%. A total of 66 genes were annotated, including 39 protein-coding genes, 24 transfer RNA genes, and 3 ribosomal RNA genes; 15 genes contained 27 introns, and three copies of trnM-CAT were identified. Codon usage analysis showed a strong preference for A/U-ending codons, with UUA as the most frequently used optimal codon. A total of 133 predicted C-to-T RNA editing sites were detected in 34 of the 39 protein-coding genes, predominantly at the first and second codon positions, and many editing events altered amino-acid hydrophobicity. Repeat analysis identified 51 dispersed repeats, five tandem repeats, and 110 simple sequence repeats. Comparative analyses revealed several highly variable regions, including ccmFC\u0026ndash;rps4 and nad6\u0026ndash;cox2, and five loci with relatively high nucleotide diversity. Phylogenetic analysis recovered \u003cem\u003eGrimmia tergestina\u003c/em\u003e as the basal lineage of the sampled Grimmiaceae, whereas Funaria hygrometrica and Physcomitrium patens formed a basal outgroup clade. In addition, 38 high-confidence homologous fragments were detected between mitochondrial and chloroplast genomes, most of which were rRNA-derived.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThese results provide the first comprehensive mitochondrial genome resource for \u003cem\u003eGrimmia tergestina\u003c/em\u003e and show that its organellar genome evolution is characterized by A/U-biased codon usage, abundant RNA editing, repeat-rich intergenic regions, and detectable chloroplast-to-mitochondrion sequence transfer. The study provides useful genomic evidence for future investigations of bryophyte molecular evolution, phylogeny, and organelle genome coordination.\u003c/p\u003e","manuscriptTitle":"Comprehensive Analysis of the Mitochondrial Genome of Grimmia tergestina: Codon Usage Bias, RNA Editing, and Organelle DNA Transfer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-21 16:27:20","doi":"10.21203/rs.3.rs-9311791/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"5243502625054305805712622096922064982","date":"2026-05-08T10:52:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T07:22:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"338866301161937335834780213559353607118","date":"2026-04-24T02:07:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-13T10:12:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-13T10:01:25+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-07T09:26:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-07T08:22:46+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Plant Biology","date":"2026-04-07T07:28:19+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-plant-biology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pbio","sideBox":"Learn more about [BMC Plant Biology](http://bmcplantbiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pbio/default.aspx","title":"BMC Plant Biology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8c6338db-acb8-43da-8391-2f4730bb59d3","owner":[],"postedDate":"April 21st, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"5243502625054305805712622096922064982","date":"2026-05-08T10:52:39+00:00","index":139,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-07T07:22:29+00:00","index":138,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-21T16:27:20+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-21 16:27:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9311791","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9311791","identity":"rs-9311791","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}